Update CI#76
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- updated actions to recent major versions - updated python-version to 3.14 or 3.13 - removed deprecated macos-13 runner and replaced macos-15-intel - removed tested Python 3.9 and 3.10 and added 3.13 and 3.14
- removed from CI - removed from RTD
Use update from PR #70.
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- deploy Python 3.11 - 3.14 packages - updated macos intel images - fixed incorrect action upload -> download
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The windows runners fail when re-installing MDAnalysis. It looks as if the mamba line just doesn't do anything: The above should install something, right? When we then try to import then there's no MDAnalysis package. |
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The windows/mamba failure is fixed by setting |
- update the license identifier - update the supported Python versions: 3.11 - 3.14
- runs locally twin 6.2.0 - fails as part of CI (also 6.2.0)
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Deploy testing
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Currently, deployment requires explicit approval, which slows things down a bit and I am not sure if the extra security is needed. I am not a maintainer here so I am not going to change that but wanted to at least let @MDAnalysis/encore folks know. |
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@enoee @yuxuanzhuang this PR updates the CI so that both tests and deployments work again. It also raises the supported Python versions to 3.11-3.14. Once this is merged, we can look at #72 and the PR #78 to see if they are still needed. Either way, we can then make a 1.0.1 release that should hopefully work again on all platforms and on all recent Pythons. Please have a quick look. Once you're happy, I'll squash-merge. |
enoee
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Thanks a lot for doing this, I have no comments
We are not building macos x86_64 wheels so we should use the M1 runner
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The current deployment had an inconsistency because I had not understood how pypa/cibuildwheel was driven. In order to produce arm64 wheels we should (probably) not use macos15-intel but macos-15 (see the images for public runners). For comparison, it was interesting to see how scikit-learn builds wheels. |
| uses: conda-incubator/setup-miniconda@v4 | ||
| with: | ||
| python-version: 3.11 | ||
| python-version: 3.14 |
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I'm shadowing your changes here.
Since I’m not very familiar with this action (or conda in general), I wanted to ask: is this python-version meant to target the latest Python version? I’m wondering whether it might be better to target the oldest supported version instead, then if it works with the min supported here -3.11-, it should also work for newer versions.
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I don't think it matters as it really only needs to build the docs. I just bumped it up so that it will be 2 years until someone has to bump it up again...
Generally the recommendation is to keep the approval step - it's what we do in the core library. You don't want anyone attempting to trigger a release without maintainer approval. |
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Ok, thanks for the advice. I suppose anyone can git-tag and that triggers the test-pypi deployment, which is then stopped through the approval action (or is git-tag functionality restricted?) |
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Leave the branch alive. I used 1.0.1rc[12] tags during testing and these tags (and releases) point to commits on this branch. We should probably eventually remove all of them (including testpypi and pypi).... |
Fixes https://github.com/MDAnalysis/mdaencore/security/dependabot/2
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